USING NONPARAMETRIC TESTS TO EVALUATE TRAFFIC FORECASTING PERFORMANCE

This paper proposes the use of a number of nonparametric comparison methods for evaluating traffic flow forecasting techniques. The advantage to these methods is that they are free of any distributional assumptions and can be legitimately used on small datasets. To demonstrate the applicability of these tests, a number of models for the forecasting of traffic flows are developed. The one-step-ahead forecasts produced are then assessed using nonparametric methods. Consideration is given as to whether a method is universally good or good at reproducing a particular aspect of the original series. That choice will be dictated, to a degree, by the user's purpose for assessing traffic flow.

• Record URL:
  • http://www.bts.gov/publications/journal_of_transportation_statistics/volume_05_number_01/
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/37387952
• Corporate Authors:

  Research and Innovative Technology Administration

  Bureau of Transportation Statistics, 1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • CLARK, S D
  • Grant-Muller, Susan M
  • Chen, Huanlei
• Publication Date: 2002

Language

• English

Media Info

• Features: Figures; References; Tables;
• Pagination: p. 47-56
• Serial:
  • Journal of Transportation and Statistics
  • Volume: 5
  • Issue Number: 1
  • Publisher: Research and Innovative Technology Administration
  • ISSN: 1094-8848
  • Serial URL: http://www.bts.gov/publications/journal_of_transportation_and_statistics/

Subject/Index Terms

• TRT Terms: Forecasting; Nonparametric analysis; Performance evaluations; System design; Traffic flow; Traffic forecasting
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting; I73: Traffic Control;

Filing Info

• Accession Number: 00944075
• Record Type: Publication
• Files: TRIS, ATRI, USDOT
• Created Date: Jun 27 2003 12:00AM